我们感谢艾格尼丝的Viale博士和MSKCC基因组学核心实验室提供技术援助。此协议是从杰弗里比尼癌症研究中心和农民家庭基金会的支持下开发的。

1。 DNA和试剂制备注意:该协议描述了24个样本（ 例如，12种肿瘤/正常对）的同时进行处理和分析，但可以适用于更小和更大的批次。 DNA样本可能来自FFPE或新鲜冷冻组织，细胞学标本，或血液。通常，这两种肿瘤和正常组织的来自同一患者将异形在一起，以便从遗传多态性区分的体细胞突变。该协议将立即开始DNA提取以下。 <ol><li>等分试样50-250纳克（250纳克推荐）每个样品中提取的DNA，稀释在1x的Tris-EDTA（pH值8.0）缓冲液中，以50微升的最终体积，为单独的Covaris圆底试管中。 </li><li>剪切力对Covaris E220仪器的DNA在以下剪切设置:360秒，10占空因数，175画中画，每爆裂200次。 </li><li>解冻AMPure XP珠（ 表2）至室温。解冻所有BUffers和酶在冰上之前的适当步骤。 </li></ol> 2。文库制备 - 完维修模块<ol><li>使用每个样品以下几卷准备结束维修师傅混在一个无菌的离心管:10微升10X NEBNext结束修复反应缓冲液（ 表2），5微升NEBNext结束修复酶混合物（ 表2），35微升无菌核酸游离H 2 O。 </li><li>分装50μl的每个剪切的DNA到96孔板的单独的孔中。加入50微升的准备结束维修师傅组合到每个反应。在20℃下孵育在热循环仪进行30分钟</li></ol> 3。结束后的修复清理<ol><li>添加AMPure XP珠（ 表2）的2倍体积（200微升），以每个样品，并使用多道移液器轻轻地吸取了整个音量向上和向下10倍。在室温下孵育15分钟。 </li><li>广场上的磁性支架（ 表2 </STRONG&gt;），在室温下15分钟，直到样品出现明显的。 </li><li>轻轻取出并丢弃上清液，注意不要打扰珠。一些液体可能会留在井中。 </li><li>与在支架管，轻轻地加入200微升新鲜制备的80％乙醇中的每个样品，孵育板在室温下持续30秒。小心，通过吸管除去乙醇。 </li><li>重复步骤5，共2乙醇洗涤。确保所有的乙醇已被删除。从磁性支架取出，放于干燥室温下5分钟。 </li><li>重悬干燥珠粒与44.5微升无菌H 2 O。轻轻地，移液管整个音量上下10X充分混合。确保珠粒不再连接到井的侧面。 </li><li>孵育再悬浮珠粒在室温下持续2分钟。将磁静置5分钟，直到样品出现明显的。 </li><li>轻轻地转移42微升含有样品到一个新的好清楚上清液。 该程序可以安全地停在这个STEP并储存在-20℃下7天的样品。要重新启动，继续操作前解冻冷冻样本置于冰上。 </li></ol> 4。文库制备 - DA-泰陵模块<ol><li> 5微升10倍NEBNext大拖尾反应缓冲液（ 表2），3微升（3&#39;-5&#39;外切）Klenow片段（ 表2:使用每样以下几卷准备大拖尾预混液在无菌的离心管）。 </li><li>加入8μL准备好的大拖尾主结构，每孔含42微升的最终修复的DNA。在37℃下孵育在热循环仪进行30分钟</li><li>执行后大拖尾清理:用无菌H 2 O至33.75微升，最终体积2倍体积（100微升）的珠子，但重悬，重复步骤3.1-3.8。 该程序可以安全地停止在该步骤中，保存于-20℃下进行长达7天的样品。要重新启动，解冻冷冻样品上，然后再继续冰。&lt;/ LI&gt; </ol> 5。文库制备 - 接头连接模块<ol><li> 10微升5倍NEBNext快速连接反应缓冲液（New England Biolabs公司， 表2），5微升快速T4 DNA连接酶（ 表2）:使用每个样本以下几卷准备结扎预混液在无菌的离心管。 </li><li>加入15微升连接主结构，每孔含DA尾的DNA。 </li><li>加入1.25微升适当的25微米NEXTflex条形码适配器（ 表2），每孔。每个样品应接受一个单独的条形码适配器。在20℃下孵育在热循环仪进行15分钟</li><li>在无菌H 2 O的使用珠1X体积（50μL）重复步骤3.1-3.8，但重悬至50微升，最终体积:执行后接头连接清理。 </li><li>对于第二个1X卷（50微升）清理重复步骤3.1-3.8，但重悬在无菌H 2 O至一23微升最终体积。 该程序可以安全地停止在该步骤中，保存于-20℃下进行长达7天的样品。要重新启动，继续操作前解冻冷冻样本置于冰上。 </li></ol> 6。文库扩增<ol><li>准备KAPA高保真主结构中使用下列卷每个样品的无菌微量离心管:25微升2倍KAPA高保真HS马币（ 表2），每个100μM引物1和2（ 表3），1微升。 </li><li>加27微升主混合物到每个孔中含有的连接产物。设置吸至50μl，轻轻吸取整个音量上下10倍。 </li><li>放置在热循环仪中进行以下PCR循环:45秒，在98℃初始变性，10个循环15秒，在98℃，30秒，60℃，30秒，72℃，1分钟的最终延伸在72°C。 </li><li>进行扩增后的清理:使用重复步骤3.1-3.8AMPure XP珠的1X卷（50微升），重悬在无菌水中，以30微升的最终体积。 </li><li>量化每个库的根据制造商的说明书，使用量子比特宽范围测定（Life Technologies公司， 表2）的浓度。 </li></ol> 7。罗氏NimbleGen SeqCap的EZ图书馆杂交，洗涤和扩增<ol><li>解冻普及和指数寡核苷酸阻断剂（ 表3），SeqCap的EZ图书馆和NimbleGen的捕捉组件（COT的DNA，2个杂交液，杂交和成分A， 表2），在冰上。所有的寡核苷酸阻断剂都存放在1毫米工作股。我们SeqCap的EZ图书馆是捕获探针涵盖的279癌症相关基因的所有蛋白质编码外显子，但是可以使用其他自定义和目录设计定制设计的游泳池。 </li><li>准备对应于所述特定条形码的广告索引寡核苷酸阻断剂的1 mM的池在文库制备用于aptor序列。结合1μl的各阻断剂，和涡流。 </li><li>在一个新的无菌的1.5 ml离心管中，加入5微升1mg/ml的COT的DNA，2微升1毫米通用阻滞剂和2微升指数寡核苷酸阻断剂的1 mM的游泳池。 </li><li>池24条形码库到一个单一的反应。一共有1-3微克汇集，条形码序列库（上述制备）加入到捕捉混合物中。对于24个样品，每个样品100纳克建议。当汇集肿瘤和匹配的正常样本，我们建议增加更多的肿瘤库（ 如每个肿瘤和正常每50毫微克100毫微克），使它们测序，以更深入的报道。 </li><li>关闭该管帽，使15-20的孔中具有18-20 G或更小的针帽的顶部。 Speed​​ Vac中扩增样本库/ COT DNA /在高温（60℃）的DNA真空浓缩寡核苷酸。 </li><li>一旦完全干燥下来，补充水分与7.5微升2倍的有杂交zation缓冲液和3微升杂交组分A的管现在应包含以下内容:5微克（COT）的DNA，可变微克放大样品库1000皮摩尔通用和指数寡核苷酸，7.5微升2×杂交缓冲液，在3微升杂交A组份10.5μl总体积。 </li><li>覆盖在帽上的孔与一小块实验室胶带。旋涡样，持续10秒，并以最大速度离心10秒。 </li><li>孵育样品在95℃下10分钟以使DNA变性，然后离心以最大的速度持续10秒在RT。 </li><li>在新0.2毫升的PCR条管，准备SeqCap的EZ图书馆捕获探针和2.25微升无菌无核酸酶的H 2 O的的2.25微升等分，并添加7.7步的内容。轻轻吸取整个音量上下10倍。 </li><li>孵育在热循环仪在47℃下进行48-96小时。设置和维护的热循环仪的盖子温度为57°C。 </li><li>折伞在NimbleGen的SeqCap的EX图书馆SR用户指南V3.0（ 表2）进行洗涤和捕获的DNA的回收第6章低步骤。 </li><li>如下在罗氏NimbleGen协议所捕获的DNA进行了以下修改的放大的第7步: <ul type="disc"><li>使用2个KAPA高保真聚合酶代替的Phusion高保真PCR扩增预混试剂（ 见表2） </li><li>使用100μM的引物1和引物2在表3中列出。 </li><li>运行以下PCR条件:在98℃起始变性30秒，11个循环的98℃10秒，60℃30秒，72℃30秒，72℃最后延伸5分钟。保持在4°C。 </li></ul></li><li>量化，根据制造商的说明使用量子比特的高灵敏度测定（ 表2）的扩增捕获的DNA的浓度。 </li><li>分析使用安捷伦Bio捕获DNA的质量分析器的DNA芯片HS（ 表2）按照制造商的说明。 <ul type="disc"><li>将PCR产率至少应为100毫微克（范围100-1000毫微克）。 </li><li>的平均片段长度应该是150-400个碱基对之间。 </li></ul></li></ol> 8。 Illumina公司的Hi-序列测序<ol><li>稀释扩增的DNA捕获到下午2点，并装入样品上的Illumina的HiSeq 2000流动池的单一车道。根据制造商的说明书序列配对末端75个碱基对的读取。根据我们的经验，一个车道就足以产生每个样品500-700X唯一的序列覆盖整个279基因的24个样品池。 </li><li> Illumina公司的软件（实时分析）将高分辨率的图像转换为集群强度为基础的呼叫和质量分数。使用CASAVA根据条形码的身份去复用数据，并生成单个FASTQ文件，每个样品。 </li></ol> 9。数据分析ysis <ol><li>从序列的3&#39;端修剪接头序列读取使用Cutadapt（FASTQ文件<a href="http://code.google.com/p/cutadapt/">http://code.google.com/p/cutadapt/</a> ）。最小搭接长度（-O）为3 1％的错误率（-E）。最低基数长度保持配对的修剪是25后读取。 </li><li>排列顺序来读取使用Burrows-惠勒调校工具（BWA）12参考人类基因组hg19。执行后处理步骤，包括根据自己的标准最佳实践（使用基因组分析工具包（GATK）重复的标记，当地多序列调整和基本质量得分重新校准<a href="http://www.broadinstitute.org/gatk/guide/topic?name=best-practices">http://www.broadinstitute.org/gatk/guide/topic？名称=最佳实践</a> ）13。当分析来自同一患者的多个样品（ 例如，匹配的肿瘤和正常），本地多序列调整应的perforMED联合。这些后处理步骤的输出是对每个样品，其中包含的所有序列，质量和取向信息，可直接加载到结合基因组浏览器（IGV），用于读取和序列变体14的可视化的单独的BAM文件。 </li><li>使用皮卡德工具计算序列的性能指标（ <a href="http://picard.sourceforge.net/">http://picard.sourceforge.net/</a> ）。信息化指标包括对齐率，片段大小分布，GC含量相关报道的偏见，对目标的捕获特异性，PCR重复率，库的复杂性，和平均目标覆盖。代表值被显示在图1。等位基因频率在使用DepthOfCoverage从GATK计算常见多态性位点被用来从无关的DNA污染监测，并确保匹配样本来自同一患者。 下面的计算分析依赖于匹配的存在肿瘤和正常样本进行体细胞的遗传改变的检测。无与伦比的肿瘤也可以使用一个单独的正常对照样品进行分析，但大多数的体细胞突变不能容易地从继承的序列变体区分开来。 </li><li>利用体细胞突变来电，如muTect 15，SomaticSniper 16，或Strelka 17各肿瘤对正常体细胞调用单核苷酸变异（SNVs）。我们使用muTect具有修饰的过滤标准，允许与正常样品中的低（非零）等位基因计数只要等位基因频率是至少5倍的程度，在肿瘤的变种。变种循环地称为在正常的DNA面板也将被移除排序或排列的可能系统性文物。每个SNV通过过滤器，然后仔细审查使用IGV。 </li><li>叫躯体插入缺失对每个肿瘤对正常使用的算法如SomaticIndelDetector 13，Dindel 18，或19 SOAPindel </sup&gt;。我们使用SomaticIndelDetector用以下标准:至少10％的等位基因频率与至少3支持读取，或者至少2％的等位基因频率与至少10支撑的读取。我们允许插入缺失与正常样品中的低（非零）等位基因计数只要等位基因频率是至少5倍更大的肿瘤。插入缺失称为在正常的DNA面板被去除，如上述。每个插入缺失通过过滤器，然后仔细审查使用IGV。 </li><li>从序列覆盖在目标外显子外推套数状态。对于每一个样本，为所有目标外显子，回归了GC比例进行平均序列覆盖的黄土正常化。减去黄土配合和添加样品的全覆盖中位数调整，非标准化的覆盖值。计算比例，在所有目标外显子的肿瘤对正常正规化序列覆盖率。如果没有匹配的正常样本和/或降低噪声，其他与性别相匹配的二倍体正常对照缺乏种系拷贝数变异体也可使用。确定体拷贝数得失的基础上的覆盖率增加或减少。 </li><li>调用涉及癌基因，其中至少一个基因组中断点落在范围内或附近的基因组的目标间隔体细胞重排。建议的算 ​​法包括GASV 20，Breakdancer 21，CREST 22，和dRanger 23。染色体内的倒位，缺失，和串联重复可以根据支撑的相对位置和方向读取不和谐对区别开来。所有考生重排，应人工审查使用IGV。我们建议实验验证通过在假定的重排断点PCR和Sanger测序。 </li></ol>

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L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensitive+detection+of+somatic+point+mutations+in+impure+and+heterogeneous+cancer+samples.">Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples.</a> Nat. Biotechnol. 31 (3), 213-219 (2013).</li><li>Larson, D. E., Harris, C. C., Chen, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SomaticSniper:+identification+of+somatic+point+mutations+in+whole+genome+sequencing+data.">SomaticSniper: identification of somatic point mutations in whole genome sequencing data.</a> Bioinformatics. 28 (3), 311-317 (2012).</li><li>Saunders, C. T., Wong, W. S., Swamy, S., Becq, J., Murray, L. J., Cheetham, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Strelka:+Accurate+somatic+small-variant+calling+from+sequenced+tumor-normal+sample+pairs.">Strelka: Accurate somatic small-variant calling from sequenced tumor-normal sample pairs.</a> Bioinformatics. 28 (14), 1811-1817 (2012).</li><li>Albers, C. A., Lunter, G., Macarthur, D. G., Mcvean, G., Ouwehand, W. H., Din del Durbin, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+indel+calls+from+short-read+data.">Accurate indel calls from short-read data.</a> Genome Res. 21 (6), 961-973 (2011).</li><li>Li, S., Li, R., Li, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficient+identification+of+indels+from+short+paired+reads.">Efficient identification of indels from short paired reads.</a> Genome Res. 23 (1), 195-200 (2013).</li><li>Sindi, S., Helman, E., Bashir, A., Raphael, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+geometric+approach+for+classification+and+comparison+of+structural+variants.">A geometric approach for classification and comparison of structural variants.</a> Bioinformatics. 25 (12), 222-230 (2009).</li><li>Chen, K., Wallis, J. W., Mclellan, M. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BreakDancer:+an+algorithm+for+high-resolution+mapping+of+genomic+structural+variation.">BreakDancer: an algorithm for high-resolution mapping of genomic structural variation.</a> Nat. Methods. 6 (9), 677-681 (2009).</li><li>Wang, J., Mullighan, C. G., Easton, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CREST+maps+somatic+structural+variation+in+cancer+genomes+with+base-pair+resolution.">CREST maps somatic structural variation in cancer genomes with base-pair resolution.</a> Nat. Methods. 8 (8), 652-654 (2011).</li><li>Drier, Y., Lawrence, M. S., Carter, S. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Somatic+rearrangements+across+cancer+reveal+classes+of+samples+with+distinct+patterns+of+DNA+breakage+and+rearrangement-induced+hypermutability.">Somatic rearrangements across cancer reveal classes of samples with distinct patterns of DNA breakage and rearrangement-induced hypermutability.</a> Genome Res. 23 (2), 228-235 (2012).</li><li>Wang, Z., Gerstein, M., Snyder, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-Seq:+a+revolutionary+tool+for+transcriptomics.">RNA-Seq: a revolutionary tool for transcriptomics.</a> Nat. Rev. Genet. 10 (1), 57-63 (2009).</li><li>Roychowdhury, S., Iyer, M. K., Robinson, D. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Personalized+oncology+through+integrative+high-throughput+sequencing:+a+pilot+study.">Personalized oncology through integrative high-throughput sequencing: a pilot study.</a> Sci. Transl. Med. 3 (111), 111ra121 (2011).</li><li>Kerick, M., Isau, M., Timmermann, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+high+throughput+sequencing+in+clinical+cancer+settings:+formaldehyde+fixed-paraffin+embedded+(FFPE)+tumor+tissues,+input+amount+and+tumor+heterogeneity.">Targeted high throughput sequencing in clinical cancer settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity.</a> BMC Med. Genomics. 4, 68 (2011).</li></ol>

Berger博士已收到的咨询费和科研经费从基础医学，癌症诊断公司。

我们的影响分析产生的高定位速度，较高的目标速度，目标高覆盖，高灵敏度检测基因突变，插入缺失和拷贝数变化。我们已经证明我们的影响分析的能力，同时从新鲜冰冻的DNA序列和归档低的DNA输入FFPE样品。通过执行主要癌症相关的基因有针对性的外显子测序，可以达到非常深的序列覆盖率为这些最关键的基因的外显子从而最大限度地检测低频率突变的能力。使用条形码和复用的，可实现更高...

在关键的癌基因和肿瘤抑制基因的"驱动器"肿瘤的遗传事件的识别起着许多癌症1的诊断和治疗的重要作用。利用大规模并行"下一代"测序大规模的研究工作已经启用了很多这样的癌症相关的基因，近年来2的鉴定。然而，这些测序平台通常需要大量的DNA从新鲜冰冻组织中分离，从而构成一个重大的限制在从保存组织，如福尔马林固定，石蜡包埋（FFPE）的肿瘤样品表征和分析DNA突变。改进的努力，高效，可靠地从FFPE肿瘤样本的特征"可操作的"基因组信息将使以前存入银行的标本进行回顾性分析，并进一步鼓励个性化的方法对癌症的管理。 传统上，分子ðiagnostic实验室一直依赖耗时，低通量的方法，如Sanger测序及实时荧光定量PCR进行DNA突变分析。最近，利用复用PCR或质谱基因分型高通量方法已被开发来调查在关键的癌基因3-5复发性体细胞突变。这些方法，但是，只有预先指定的"热点"的突变进行了检测，使得它们不适合用于检测失活突变的肿瘤抑制基因受到限制。大规模并行测序提供了这些策略的几个优点，包括审问整个外显子为双方共同和稀有突变的能力，才能看到其他类基因组改变，如拷贝数收益和损失的能力，异构样品6，在更高的检测灵敏度7 。全基因组测序为代表的突变的发现的最全面的方法，虽然它是相对的LY昂贵，即被用于数据分析和存储大量的计算需求。 对于临床应用，其中的基因组中的仅一小部分可能是临床利益，在测序技术2特别的创新已经变革。首先，通过基于杂交的外显子捕获，可以分离DNA对应键与癌症相关的基因突变有针对性的分析8。第二，通过分子条形码（ 即 DNA序列的6-8个核苷酸长）的结扎，可以有数百个每个测序运行样品并充分利用大规模并行测序仪器10不断增加的容量的优点。合并后，这些创新使肿瘤可为异形更低的成本和更高的吞吐量，更小的计算需求11。进一步，通过重新分配序列覆盖，只有那些基因最关键的特定应用，可以achie已经较大的测序深度为低等位基因频率较高的事件检测灵敏度。 在这里，我们描述了我们的影响分析（中可操作的癌症靶点整合突变图谱），使用自定义的寡核苷酸捕获所有蛋白质编码外显子和选择的279键的癌症相关基因的内含子（它利用外显子捕获的条形码序列库池通过杂交表1 ）。这一战略使基因突变，插入缺失，拷贝数改变的识别，并选择涉及这些279个基因的结构重排。我们的方法是与DNA来自新鲜冷冻和FFPE组织以及细针抽吸等细胞学标本中分离出兼容。

<table><tbody><tr><td>NEBNext End Repair Module</td><td>New England Biolabs</td><td>E6050L</td><td>&amp;nbsp;</td></tr><tr><td>NEBNext dA-Tailing Module</td><td>New England Biolabs</td><td>E6053L</td><td>&amp;nbsp;</td></tr><tr><td>NEBNext Quick Ligation Module</td><td>New England Biolabs</td><td>E6056L</td><td>&amp;nbsp;</td></tr><tr><td>Agencourt AMPure XP</td><td>Beckman Coulter Genomics</td><td></td><td>&amp;nbsp;</td></tr><tr><td>NEXTflex PCR-Free Barcodes &amp;ndash; 24</td><td>Bioo Scientific</td><td>514103</td><td>&amp;nbsp;</td></tr><tr><td>HiFi Library Amplification Kit</td><td>KAPA Biosystems</td><td>KK2612</td><td>&amp;nbsp;</td></tr><tr><td>COT Human DNA, Fluorometric Grade</td><td>Roche Diagnostics</td><td>05 480 647 001</td><td>&amp;nbsp;</td></tr><tr><td>NimbleGen SeqCap EZ Hybridization and Wash kit</td><td>Roche NimbleGen</td><td>05 634 261 001</td><td>&amp;nbsp;</td></tr><tr><td>SeqCap EZ Library Baits</td><td>Roche NimbleGen</td><td></td><td>&amp;nbsp;</td></tr><tr><td>QIAquick PCR Purification Kit</td><td>Qiagen</td><td>28104</td><td>&amp;nbsp;</td></tr><tr><td>Qubit dsDNA Broad Range (BR) Assay Kit</td><td>Life Technologies</td><td>Q32850</td><td>&amp;nbsp;</td></tr><tr><td>Qubit dsDNA High Sensitivity (HS) Assay Kit</td><td>Life Technologies</td><td>Q32851</td><td>&amp;nbsp;</td></tr><tr><td>Agilent DNA HS Kit</td><td>Agilent Technologies</td><td>5067-4626, 4627</td><td>&amp;nbsp;</td></tr><tr><td>Agilent 2100 Bioanalyzer</td><td>Agilent Technologies</td><td></td><td>&amp;nbsp;</td></tr><tr><td>Covaris E220</td><td>Covaris</td><td></td><td>&amp;nbsp;</td></tr><tr><td>Magnetic Stand-96</td><td>Ambion</td><td>AM10027</td><td>&amp;nbsp;</td></tr><tr><td>Illumina Hi-Seq 2000</td><td>Illumina</td><td></td><td>&amp;nbsp;</td></tr></tbody></table>

detecting somatic genetic alterations in tumor specimens by exon capture and massively parallel sequencing

努力发现和调查的关键致癌基因突变已被证明有价值的，以方便对癌症患者进行相应的处理。高通量的建立，大规模并行"下一代"测序已经资助了许多这样的突变的发现。以提高该技术的临床和平移工具，平台必须是高通量，成本效益，并用福尔马林固定，石蜡包埋（FFPE）组织样品可能产生少量的退化或受损的DNA兼容。在这里，我们描述了随后靶向外显子用于癌症相关的突变在新鲜冰冻和石蜡包埋的肿瘤通过大规模平行测序检测的基于杂交的捕获条形码和复用DNA文库的制备。这种方法使序列突变的识别，拷贝数变化，并选择涉及所有目标基因的结构重排。针对外显子测序提供吨他同样拥有高通量，低成本，和深序列覆盖率，从而赋予高灵敏度检测低频率突变。

使用对应于279癌基因的所有蛋白质编码外显子探针24条形码序列库（12肿瘤对正常）一池被抓获，并测序为2×75 bp的读取上一个的HiSeq 2000流动池的单一车道。肿瘤和正常库汇集以2:1的比例。冷冻肿瘤DNA样品的样品池的性能指标示于图1，其中包括对应率，片段大小分布，对靶标捕获的特异性，和平均目标覆盖范围。例如体细胞突变，插入，缺失和拷贝数改变的示于图2-4中 。...

Watch this Scientific Journal Video about Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing at JoVE.com

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

我们描述条形码DNA文库和随后的杂交为基础的外显子捕获检测的关键癌症相关的基因突变在临床肿瘤标本通过大规模并行的"下一代"测序的准备。靶向外显子的测序提供了高吞吐量，低成本，以及深的序列覆盖率的好处，从而产生较高的灵敏度，用于检测低频率突变。

由外显子捕获和大规模平行测序检测体细胞遗传学改变在肿瘤标本

Efforts  to detect and investigate key oncogenic mutations have proven valuable to  facilitate the appropriate treatment for cancer patients. The ...

detecting-somatic-genetic-alterations-tumor-specimens-exon-capture

Research

JoVE Journal

Biology

19.3K 次观看.  Memorial Sloan-Kettering Cancer Center. 我们描述条形码DNA文库和随后的杂交为基础的外显子捕获检测的关键癌症相关的基因突变在临床肿瘤标本通过大规模并行的"下一代"测序的准备。靶向外显子的测序提供了高吞吐量，低成本，以及深的序列覆盖率的好处，从而产生较高的灵敏度，用于检测低频率突变。 

视频: Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific molecular profiles of a tumor may predict responsiveness to therapeutic agents or provide knowledge about prognosis. At our institution a tumor genotyping program was established as part of routine clinical care, screening both hematologic and solid tumors for a wide spectrum of mutations using two next-generation sequencing (NGS) panels: a custom, 33 gene hematological malignancies panel for use with peripheral blood and bone marrow, and a commercially produced solid tumor panel for use with formalin-fixed paraffin-embedded tissue that targets 47 genes commonly mutated in cancer. Our workflow includes a pathologist review of the biopsy to ensure there is adequate amount of tumor for the assay followed by customized DNA extraction is performed on the specimen. Quality control of the specimen includes steps for quantity, quality and integrity and only after the extracted DNA passes these metrics an amplicon library is generated and sequenced. The resulting data is analyzed through an in-house bioinformatics pipeline and the variants are reviewed and interpreted for pathogenicity. Here we provide a snapshot of the utility of each panel using two clinical cases to provide insight into how a well-designed NGS workflow can contribute to optimizing clinical outcomes.

This manuscript describes clinical protocols for two next-generation sequencing panels. One panel interrogates hematologic malignancies while the other panel targets genes commonly mutated in solid tumors. Molecular classification of driver mutations in human malignancies offers valuable prognostic and predictive information.

新一代测序为可操作的突变在固体和液体瘤检测

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific ...

科研

癌症研究

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. However, the application of this method is challenging due to its low sensitivity in analyzing the trace amount of ctDNA in the blood. Furthermore, the method may generate false positive and negative results from this sequencing and subsequent analysis. To improve the feasibility and reliability of ctDNA detection in the clinic, here we present a technique which enriches rare mutations for sequencing, Enrich Rare Mutation Sequencing (ER-Seq). ER-Seq can distinguish a single mutation out of 1 x 107 wild-type nucleotides, which makes it a promising tool to detect extremely low frequency genetic alterations and thus will be very useful in studying disease heterogenicity. By virtue of the unique sequencing adapter&#39;s ligation, this method enables an efficient recovery of ctDNA molecules, while at the same time correcting for errors bidirectionally (sense and antisense). Our selection of 1021 kb probes enriches the measurement of target regions that cover over 95% of the tumor-related driver mutations in 12 tumors. This cost-effective and universal method enables a uniquely successful accumulation of genetic data. After efficiently filtering out background error, ER-seq can precisely detect rare mutations. Using a case study, we present a detailed protocol demonstrating probe design, library construction, and target DNA capture methodologies, while also including the data analysis workflow. The process to carry out this method typically takes 1-2 days.

This manuscript describes a technique for detecting mutations of low frequency in ctDNA, ER-Seq. This method is differentiated by its unique use of two-directional error correction, a special background filter, and efficient molecular acquirement.

利用下一代测序检测 CtDNA 中的稀有突变

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. ...

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissues are widely used for genetic testing. However, FFPE DNA is generally damaged and fragmented during the fixation process with formalin. Therefore, FFPE DNA is sometimes not adequate for genetic testing because of low quality and quantity of DNA. Here we present a method of touch imprint cytology (TIC) to obtain genomic DNA from cancer cells, which can be observed under a microscope. Cell morphology and cancer cell numbers can be evaluated using TIC specimens. Furthermore, the extraction of genomic DNA from TIC samples can be completed within two days. The total amount and quality of TIC DNA obtained using this method was higher than that of FFPE DNA. This rapid and simple method allows researchers to obtain high-quality DNA for genetic testing (e.g., next generation sequencing analysis, digital PCR, and quantitative real time PCR) and to shorten the turnaround time for reporting results.

Obtaining high-quality genomic DNA from tumor tissues is an essential first step for analyzing genetic alterations using next generation sequencing. In this article, we present a simple and rapid method to enrich tumor cells and obtain intact DNA from touch imprint cytology specimens.

用触印细胞学方法快速获得临床病理标本中高质量肿瘤 DNA

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. ...

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in&#160;patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.

Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.

患者生物流体中肿瘤相关循环DNA的检测与监测

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular ...

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples from cancer patients often directly influences diagnosis, prognosis, and/or therapy selection. As a result, the accurate detection of gene fusions has become a critical component of clinical management for many disease types. Until recently, clinical gene fusion detection was predominantly accomplished through the use of single-gene assays. However, the ever-growing list of gene fusions with clinical significance has created a need for assessing fusion status of multiple genes simultaneously. Next generation sequencing (NGS)-based testing has met this demand through the ability to sequence nucleic acid in massively parallel fashion. Multiple NGS-based approaches that employ different strategies for gene target enrichment are now available for use in clinical molecular diagnostics, each with its own strengths and weaknesses. This article describes the use of anchored multiplex PCR (AMP)-based target enrichment and library preparation followed by NGS to assess for gene fusions in clinical solid tumor specimens. AMP is unique among amplicon-based enrichment approaches in that it identifies gene fusions regardless of the identity of the fusion partner. Detailed here are both the wet-bench and data analysis steps that ensure accurate gene fusion detection from clinical samples.

This article details the use of an anchored multiplex polymerase chain reaction-based library preparation kit followed by next-generation sequencing to assess for oncogenic gene fusions in clinical solid tumor samples. Both wet-bench and data analysis steps are described.

使用锚定多路聚合酶链反应的致癌基因融合检测,随后进行下一代测序

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples ...

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic target analyses and drug response monitoring using patient derived xenografts (PDX). This strategy was validated using ovarian tumors as an example. The mate-pair next generation sequencing (MPseq) protocol was used to identify structural alterations and followed by analysis of potentially targetable alterations. Human tumors grown in immunocompromised mice were treated with drugs selected based on the genomic analyses. Results demonstrated a good correlation between the predicted and the observed responses in the PDX model. The presented approach can be used to test the efficacy of combination treatments and aid personalized treatment for patients with recurrent cancer, specifically in cases when standard therapy fails and there is a need to use drugs off label.

Here we present a protocol to test the efficacy of targeted therapies selected based on the genomic makeup of a tumor. The protocol describes identification and validation of structural DNA rearrangements, engraftment of patients&#8217; tumors into mice and testing responses to corresponding drugs.

使用结构DNA改变分析和患者衍生异种移植测试癌症的靶向疗法

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic ...

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective anti-tumor strategies. Although concerns are frequently raised due to differences in sample processing and depth of coverage, next-generation sequencing of solid tumors have unraveled a highly variable degree of ITH across tumor types. Capturing the genetic relatedness between primary and metastatic lesions through the identification of clonal and subclonal populations is critical to the design of therapies for advance-stage diseases. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same patient. The experimental approach described here integrates three well-established approaches: histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses. In order to minimize the effects on the detection of subclonal events by inappropriate sample processing, we subjected tissues to careful pathological examination and neoplastic cell enrichment. Quality controlled DNA from neoplastic lesions and normal tissues was then subjected to high coverage sequencing, targeting the coding regions of 409 relevant cancer genes. While only looking at a limited genomic space, our approach enables evaluating the extent of heterogeneity among somatic alterations (single-nucleotide mutations and copy-number variations) in distinct lesions from a given patient. Through comparative analysis of sequencing data, we were able to distinguish clonal vs. subclonal alterations. The majority of ITH is often ascribed to passenger mutations; therefore, we also used immunohistochemistry to predict functional consequences of mutations. While this protocol has been applied to a specific tumor type, we anticipate that the methodology described here is broadly applicable to other solid tumor types.

This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.

通过有针对性的测序方法进行比较病变分析

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective ...

行为学

增强癌症组织样本中致癌驱动因素的 FISH 分析

Robust Detection of Gene Amplification in Formalin-Fixed Paraffin-Embedded Samples by Fluorescence In Situ Hybridization

Focal gene amplification, such as extrachromosomal DNA (ecDNA), plays an important role in cancer development and therapy resistance. While sequencing-based methodologies enable an unbiased identification of ecDNA, cytogenetic-based techniques, such as fluorescence in situ hybridization (FISH), remain time and cost-effective for identifying ecDNA in clinical specimens. The application of FISH in formalin-fixed paraffin-embedded (FFPE) tissue samples offers a unique avenue for detecting amplified genes, particularly when viable specimens are not available for karyotype examination. However, there is a lack of consensus procedures for this technique. This protocol provides comprehensive, fully optimized, step-by-step instructions for conducting FISH to detect gene amplification, including ecDNA, in FFPE tissue samples which present unique challenges that this protocol aims to overcome and standardize. By following this protocol, researchers can reproducibly acquire high-quality imaging data to assess gene amplification.

作者聚焦：FISH 作为癌症标本中精确基因扩增评估的工具

This protocol provides a reproducible method to visualize gene amplification in formalin-fixed paraffin-embedded (FFPE) tissue specimens.

由外显子捕获和大规模平行测序检测体细胞遗传学改变在肿瘤标本

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此视频中的章节

新一代测序为可操作的突变在固体和液体瘤检测

利用下一代测序检测 CtDNA 中的稀有突变

用触印细胞学方法快速获得临床病理标本中高质量肿瘤 DNA

患者生物流体中肿瘤相关循环DNA的检测与监测

使用锚定多路聚合酶链反应的致癌基因融合检测,随后进行下一代测序

使用结构DNA改变分析和患者衍生异种移植测试癌症的靶向疗法

通过有针对性的测序方法进行比较病变分析

通过荧光原位杂交对福尔马林固定石蜡包埋样品中的基因扩增进行稳健检测

通过荧光原位杂交对福尔马林固定石蜡包埋样品中的基因扩增进行稳健检测

通过荧光原位杂交对福尔马林固定石蜡包埋样品中的基因扩增进行稳健检测